Computer Science: Recent submissions
Now showing items 181-200 of 549
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Emotion as an emergent phenomenon of the neurocomputational energy regulation mechanism of a cognitive agent in a decision-making task
(Sage, 2021-02)Biological agents need to complete perception-action cycles to perform various cognitive and biological tasks such as maximizing their wellbeing and their chances of genetic continuation. However, the processes performed ... -
Would you imagine yourself negotiating with a robot, Jennifer? Why not?
(IEEE, 2022-02)With the improvement of intelligent systems and robotics, social robots are becoming part of our society. To accomplish complex tasks, robots and humans may need to collaborate, and when necessary, they need to negotiate ... -
FedADC: Accelerated federated learning with drift control
(IEEE, 2021)Federated learning (FL) has become de facto framework for collaborative learning among edge devices with privacy concern. The core of the FL strategy is the use of stochastic gradient descent (SGD) in a distributed manner. ... -
Common media client data (CMCD): Initial findings
(Association for Computing Machinery, Inc, 2021-07-16)In September 2020, the Consumer Technology Association (CTA) published the CTA-5004: Common Media Client Data (CMCD) specification. Using this specification, a media client can convey certain information to the content ... -
Campaign participation prediction with deep learning
(Elsevier, 2021-08)Increasingly, on-demand nature of customer interactions put pressure on companies to build real-time campaign management systems. Instead of having managers to decide on the campaign rules, such as, when, how and whom to ... -
Dropout regularization in hierarchical mixture of experts
(Elsevier, 2021-01-02)Dropout is a very effective method in preventing overfitting and has become the go-to regularizer for multi-layer neural networks in recent years. Hierarchical mixture of experts is a hierarchically gated model that defines ... -
MaLeFICE: Machine learning support for continuous performance improvement in computational engineering
(Wiley, 2022-04-25)Computer aided engineering (CAE) practices improved drastically within the last decade due to ease of access to computing resources and open-source software. However, increasing complexity of hardware and software settings ... -
On the use of evolutionary coupling for software architecture recovery
(IEEE, 2021)Software architecture documentation can be partially obtained automatically by means of software architecture recovery tools. These tools mainly cluster software modules to provide a high level structural organization of ... -
Improving server and client-side algorithms for adaptive streaming of non-immersive and immersive media
(The ACM Digital Library,, 2021)HTTP adaptive streaming is a technique widely used in the internet today to stream live and on-demand content. Server and client-side algorithms play an important role in achieving a better user experience in terms of ... -
Instagram filter removal on fashionable images
(IEEE, 2021-06)Social media images are generally transformed by filtering to obtain aesthetically more pleasing appearances. However, CNNs generally fail to interpret both the image and its filtered version as the same in the visual ... -
Quaternion capsule networks
(IEEE, 2021)Capsules are grouping of neurons that allow to represent sophisticated information of a visual entity such as pose and features. In the view of this property, Capsule Networks outperform CNNs in challenging tasks like ... -
Hi–C interaction graph analysis reveals the impact of histone modifications in chromatin shape
(Springer, 2021-07-17)Chromosome conformation capture experiments such as Hi–C map the three-dimensional spatial organization of genomes in a genome-wide scale. Even though Hi–C interactions are not biased towards any of the histone modifications, ... -
Weight update skipping: Reducing training time for artificial neural networks
(IEEE, 2021-12)Artificial Neural Networks (ANNs) are known as state-of-the-art techniques in Machine Learning (ML) and have achieved outstanding results in data-intensive applications, such as recognition, classification, and segmentation. ... -
Do not predict – Recompute! How value recomputation can truly boost the performance of invisible speculation
(IEEE, 2021)Recent architectural approaches that address speculative side-channel attacks aim to prevent software from exposing the microarchitectural state changes of transient execution. The Delay-on-Miss technique is one such ... -
ANAC 2018: Repeated multilateral negotiation league
(Springer, 2020)This is an extension from a selected paper from JSAI2019. There are a number of research challenges in the field of Automated Negotiation. The Ninth International Automated Negotiating Agent Competition encourages participants ... -
Challenges and main results of the automated negotiating agents competition (ANAC) 2019
(Springer, 2020)The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. ... -
Towards automated aircraft maintenance inspection. A use case of detecting aircraft dents using mask r-cnn
(American Institute of Aeronautics and Astronautics Inc, AIAA, 2020)Deep learning can be used to automate aircraft maintenance visual inspection. This can help increase the accuracy of damage detection, reduce aircraft downtime, and help prevent inspection accidents. The objective of this ... -
Forecasting multivariate time-series data using LSTM and mini-batches
(Springer, 2020)Multivariate time-series data forecasting is a challenging task due to nonlinear interdependencies in complex industrial systems. It is crucial to model these dependencies automatically using the ability of neural networks ... -
Not all mistakes are equal
(The ACM Digital Library, 2020)In many tasks, classifiers play a fundamental role in the way an agent behaves. Most rational agents collect sensor data from the environment, classify it, and act based on that classification. Recently, deep neural networks ... -
Extraction of novel features based on histograms of mfccs used in emotion classification from generated original speech dataset
(Kauno Technologijos Universitetas, 2020-02-17)This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from ...
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